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Text Simplification
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Text Simplification is the task of reducing the complexity of the vocabulary and sentence structure of text while retaining its original meaning, with the goal of improving readability and understanding. Simplification has a variety of important societal applications, for example increasing accessibility for those with cognitive disabilities such as aphasia, dyslexia, and autism, or for non-native speakers and children with reading difficulties.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/hecta-uom/plaba-mu
공식 코드https://github.com/i-need-sleep/referee
공식 코드REFeREE: A REference-FREE Model-Based Metric for Text Simplification
https://github.com/isvy08/usdp
공식 코드https://github.com/jantrienes/InfoLossQA
공식 코드InfoLossQA: Characterizing and Recovering Information Loss in Text Simplification
https://github.com/jingjingli01/oreo
공식 코드https://github.com/jinnaiyuu/mbr-optimal-transport
공식 코드Document-Level Text Generation with Minimum Bayes Risk Decoding using Optimal Transport
https://github.com/jordiclive/ControlPrefixes
공식 코드https://github.com/kartikeypant/text-simplification-qa-www2021
공식 코드Text Simplification for Comprehension-based Question-Answering
https://github.com/lancopku/WEAN
공식 코드https://github.com/liamcripwell/plan_simp
공식 코드https://github.com/linguisticanomalies/appls
공식 코드APPLS: Evaluating Evaluation Metrics for Plain Language Summarization
https://github.com/ljyflores/simplification-project
공식 코드https://github.com/lmvasque/ts-explore
공식 코드https://github.com/lujunru/napss
공식 코드https://github.com/matejulcar/slot5-tools
공식 코드Sequence to sequence pretraining for a less-resourced Slovenian language
https://github.com/microsoft/breve-claro
공식 코드https://github.com/microsoft/unilm
공식 코드Lossless Acceleration for Seq2seq Generation with Aggressive Decoding
https://github.com/miriull/language-models-german-simplification
공식 코드https://github.com/miriull/llm-consistency-simplification
공식 코드Simpler becomes Harder: Do LLMs Exhibit a Coherent Behavior on Simplified Corpora?
https://github.com/mslars/german-text-simplification
공식 코드German Text Simplification: Finetuning Large Language Models with Semi-Synthetic Data
https://github.com/mushfiqur11/simpledc-dataset
공식 코드https://github.com/nehasrikn/elaborative-simplification
공식 코드Elaborative Simplification: Content Addition and Explanation Generation in Text Simplification
https://github.com/ninikolov/lha
공식 코드Large-scale Hierarchical Alignment for Data-driven Text Rewriting
https://github.com/njunlp/knn-box
공식 코드kNN-BOX: A Unified Framework for Nearest Neighbor Generation
https://github.com/nlp-ku/metric-based-in-context-learning
공식 코드Metric-Based In-context Learning: A Case Study in Text Simplification
https://github.com/protagolabs/seq2seq_llm_evaluation
공식 코드https://github.com/rekriz11/sockeye-recipes
공식 코드Complexity-Weighted Loss and Diverse Reranking for Sentence Simplification
https://github.com/rlsnlp/document-level-text-simplification
공식 코드Document-Level Text Simplification: Dataset, Criteria and Baseline
https://github.com/rlsnlp/simplebart
공식 코드Teaching the Pre-trained Model to Generate Simple Texts for Text Simplification
https://github.com/rlsnlp/sum4simp
공식 코드https://github.com/rstodden/deplain
공식 코드https://github.com/rstodden/easse-de
공식 코드EASSE-DE: Easier Automatic Sentence Simplification Evaluation for German
https://github.com/salesforce/simplification
공식 코드SWiPE: A Dataset for Document-Level Simplification of Wikipedia Pages
https://github.com/sallmanm/synsim
공식 코드https://github.com/sebajoe/multicochrane
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.